Embryonic development is an intrinsically multiscale phenomenon that requires a highly coordinated processes at all levels of biological organization, from genes, to proteins, to cells, to tissues and, eventually, to the whole organism. Thus, multiscale approaches are indispensable for understanding the mechanisms responsible for development. This project proposes to combine experiments and modeling to study the mechanisms by which developing epithelia are patterned by the Epidermal Growth Factor Receptor (EGFR), an evolutionary conserved regulator of tissues in animals from worms to humans. Using Drosophila melanogaster as the experimental system, the PIs will quantify the transcriptional response to EGFR signaling, develop models of EGFR-mediated cell communication in epithelial layers, and use these models to analyze the EGFR system in Drosophila oogenesis, spanning the scales from genes to organs. The experiments will combine developmental genetics, genomics, and transcriptional profiling experiments. The computational approaches will include asymptotic, homogenization, and model reduction techniques. This integrative research will lead to the first experimentally validated model of EGFR signaling in tissues. The success of this effort relies on the combined expertise of the PI at bench experiments, modeling, and analysis across developmental scales. EGFR is essential for normal tissue development, but deregulated EGFR signaling has been associated with numerous diseases, including many types of human cancers. Hence, an integrative understanding of EGFR action in tissues is of direct relevance to a wide range of medical problems. In addition to addressing the fundamental questions of cell fate diversification in development, this work will lead to computational and data integration tools for a wide range of epithelial patterning problems. First, the PIs will develop Virtual Epithelium (VE), a publicly available software for the computational analysis of epithelial patterning systems. Second, the PIs will develop and make publicly available the Database of Drosophila Oogenesis (DODO) that will combine the heterogeneous datasets generated by their experiments with bioinformatics and biostatistics tools. VE will enable systematic modeling and exploration of the spatiotemporal dynamics of cell communication by diffusible chemical signals. DODO will complement the existing database of gene expression patterns in the embryo and form a starting point for a multiscale analysis of epithelial patterning in a large number of developmental contexts. The project will bring together researchers in biology, engineering and mathematics in an interdisciplinary research program aimed at bringing about new understanding of EGFR system.